远程工作雷达

高级数据工程师(AI/ML)

Senior Data Engineer (AI/ML)

AI开发工程限定地区(需当地身份)
公司OpenTable
薪资未公开
工作地点India
地域资格限定地区(需当地身份)
时区要求日间重叠约 6 小时,基本正常作息
用工类型Full Time
发布时间今天
数据来源Himalayas
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注意地域限制:该职位明确限定在 India 招聘。如果你是位于中国大陆的求职者,通常需要当地工作身份才能投递,或需与雇主确认是否接受独立合同(Contractor)形式合作。

该职位为印度全远程办公

关于OpenTable
拥有数百万食客、70,000多家餐厅合作伙伴和25多年的经验,OpenTable是Booking Holdings, Inc.(纳斯达克:BKNG)旗下的一家行业领导者,致力于帮助餐厅蓬勃发展。我们世界级的技术使餐厅能够专注于最重要的事情——他们的团队、他们的顾客以及他们的利润,同时让食客能够发现并预订适合每种场合的完美餐厅。
OpenTable的每位员工都能对我们的工作方式产生实际影响。你还将成为全球团队及其元搜索品牌组合的一部分。餐饮业关乎照顾他人,这定义了我们的文化。

关于职位
我们正在寻找一位高级数据工程师 – AI/ML,帮助构建支持我们下一代智能产品和体验的数据和AI基础设施。
该职位结合了现代数据工程与生成式AI。你将设计可扩展的数据平台和管道,同时使用LLMs、RAG、嵌入、向量搜索和AI代理构建生产级解决方案。你将与数据科学家、ML工程师、软件工程师和产品团队紧密合作,将AI能力转化为可靠、可扩展的生产系统。

你将负责

  • 设计和构建支持训练、推理、评估、嵌入和检索工作负载的AI/LLM数据管道。
  • 构建生产级RAG系统,包括数据摄入、分块、嵌入生成、索引、检索、重新排序和上下文构建。
  • 使用LLMs、结构化输出、函数/工具调用和代理工作流开发AI应用。
  • 构建和优化语义搜索和向量检索系统。
  • 开发LLM评估、监控、追踪、质量测量、延迟和成本优化的框架。
  • 使用Databricks、Apache Spark、Delta Lake、Snowflake和Airflow设计可扩展的批处理和流式管道。
  • 构建数据产品和平台,使结构化和非结构化的企业数据可供AI应用使用。
  • 开发可靠的ETL/ELT管道,并优化大规模分布式工作负载以提高性能和降低成本。
  • 建立数据质量、治理、血缘关系、安全性和可观测性实践。
  • 与ML和应用工程团队合作,将AI原型转化为生产就绪系统。

所需资格

  • 5年以上数据工程、软件工程或相关领域的经验
查看英文原文

This role is 100% remote across India location

About OpenTable
With millions of diners, 70,000+ restaurant partners and 25+ years of experience, OpenTable, part of Booking Holdings, Inc. (NASDAQ: BKNG), is an industry leader with a passion for helping restaurants thrive. Our world-class technology empowers restaurants to focus on what matters most – their team, their guests, and their bottom line – while enabling diners to discover and book the perfect restaurant for every occasion.
Every employee at OpenTable has a tangible impact on what we do and how we do it. You’ll also be part of a global team and its portfolio of metasearch brands. Hospitality is all about taking care of others, and it defines our culture.
About Role
We are looking for a Senior Data Engineer – AI/ML to help build the data and AI infrastructure powering our next generation of intelligent products and experiences.
This role combines modern data engineering with Generative AI. You will design scalable data platforms and pipelines while building production-grade solutions using LLMs, RAG, embeddings, vector search, and AI agents. You will work closely with data scientists, ML engineers, software engineers, and product teams to turn AI capabilities into reliable, scalable production systems.
What You'll Do

  • Design and build AI/LLM data pipelines supporting training, inference, evaluation, embeddings, and retrieval workloads.
  • Build production-grade RAG systems, including ingestion, chunking, embedding generation, indexing, retrieval, reranking, and context construction.
  • Develop AI applications using LLMs, structured outputs, function/tool calling, and agentic workflows.
  • Build and optimize semantic search and vector retrieval systems.
  • Develop frameworks for LLM evaluation, monitoring, tracing, quality measurement, latency, and cost optimization.
  • Design scalable batch and streaming pipelines using Databricks, Apache Spark, Delta Lake, Snowflake, and Airflow.
  • Build data products and platforms that make structured and unstructured enterprise data accessible to AI applications.
  • Develop reliable ETL/ELT pipelines and optimize large-scale distributed workloads for performance and cost.
  • Establish data quality, governance, lineage, security, and observability practices.
  • Partner with ML and application engineering teams to move AI prototypes into production-ready systems.

Required Qualifications

  • 5+ years of experience in data engineering, software engineering, distributed systems, or a related field.
  • Strong programming skills in Python and/or Scala/Java and advanced SQL.
  • Hands-on experience with Databricks, Snowflake, Apache Spark, Delta Lake, and Airflow.
  • Strong experience with cloud data platforms such as Snowflake and/or Databricks.
  • Practical experience building applications using LLMs or Generative AI.
  • Strong understanding of RAG architectures, embeddings, vector databases, semantic search, and retrieval systems.
  • Familiarity with LLM concepts including prompting, structured outputs, tool calling, and model evaluation.
  • Experience designing scalable, reliable, and observable production data systems.

Preferred Qualifications

  • Deep experience designing large-scale data platforms, distributed processing systems, and complex data workflows.
  • Strong experience with real-time and streaming data architectures, including Kafka, Spark Structured Streaming, or similar technologies.
  • Experience building low-latency data pipelines and event-driven architectures.
  • Experience designing complex multi-stage ETL/ELT and data orchestration workflows using Airflow or similar platforms.
  • Experience optimizing Spark/Databricks workloads, including partitioning, clustering, caching, joins, and compute optimization.
  • Experience building data platforms supporting both batch and real-time AI/ML workloads.
  • Experience with LLM and AI evaluation frameworks, including automated evaluations, offline/online evaluation, quality metrics, and experimentation.
  • Experience building evaluation datasets and pipelines for measuring LLM/RAG/agent quality, accuracy, relevance, latency, and cost.
  • Experience with AI observability and tracing, including token usage, model performance, latency, failures, and production monitoring.
  • Experience with LangGraph, LangChain, LlamaIndex, or similar AI orchestration frameworks.
  • Experience with vector databases such as Qdrant, Pinecone, Weaviate, or Databricks Vector Search.
  • Experience with Kafka, MLflow, Unity Catalog, Databricks Mosaic AI, or model-serving platforms.
  • Experience building data quality, lineage, governance, and data/AI observability frameworks.
  • Strong understanding of distributed systems, cloud architecture, APIs, CI/CD, and production operations.

Impact
You will help build the data and AI foundation for intelligent products, combining large-scale data engineering, streaming systems, and modern Generative AI to deliver reliable, scalable, measurable, and production-ready AI systems.
Benefits

  • Work from (almost) anywhere for up to 20 days per year
  • Focus on mental health and well-being:
  • Company-paid therapy sessions through SpringHealth
  • Company-paid subscription to Headspace
  • Annual company-wide week off a year - the whole team fully recharges (and returns without a pile-up of work!)
  • Paid parental leave
  • Generous paid vacation + time off for your birthday
  • Paid volunteer time
  • Focus on your career growth:
  • Development Dollars
  • Leadership development
  • Access to thousands of on-demand e-learnings
  • Travel Discounts
  • Employee Resource Groups
  • Quarterly team offsites
  • Tax optimisation options
  • Generous health insurance
  • Pension fund

Work Environment & Flexibility
At OpenTable, we pride ourselves on fostering a global and dynamic work environment. As a team member with us, you will benefit from a schedule tailored to accommodate a global workforce operating across multiple time zones. While the majority of your responsibilities may align with conventional business hours, there will be instances where you are expected to manage communications - via calls, Slack messages, or emails - outside of regular working hours to effectively collaborate with international colleagues, respond to restaurant partners, and/or address urgent matters. OpenTable will always abide by and consider local laws and regulations.
Inclusion
We’re committed to creating a workplace where everyone feels they belong and can thrive. We know the best ideas come when we bring different voices to the table, so we're building a team as dynamic as the diners and restaurants we serve—and fostering a culture where everyone feels welcome to be themselves.
If you need accommodations during the application or interview process, or on the job, we’re here to support you. Please reach out to your recruiter to request any accommodations.
Originally posted on Himalayas

本页面信息整理自 Himalayas,版权归原发布方所有。职位可能随时关闭,投递请以原始页面为准。 本站只做信息聚合展示,不参与招聘流程,也不向求职者收取任何费用。

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